Instructions to use wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner") model = AutoModelForTokenClassification.from_pretrained("wietsedv/bert-base-dutch-cased-finetuned-conll2002-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d474d599e729878bf768037ea1f8cb09d8148ea118646a184e441624e2420890
- Size of remote file:
- 434 MB
- SHA256:
- 3d2d201a1c0fc5818fec18e10b7fd9bf5a2f931272e90f7ab3f8aeca9f9caf4e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.